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An Approach for Checking Grammar for Telugu Language Compound Sentences

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

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A Grammar Checking for Telugu Language Compound Sentences is one of the basic applications of the Natural Language Processing. A sentence composed of single independent clause is called a simple sentence and a sentence having more than one independent clause is a compound sentence. Once the sentence is identified as compound or complex sentence, the next step is to identify its pattern. After identification of patterns, various clauses present in the sentence are extracted and grammar checking is performed on them. For grammar checking of compound sentence, it is necessary to identify the structure of these sentences. The structure of compound sentence can be identified on the basis of number of clauses and types of clauses present in them. This study will be helpful in identifying and separating the compound sentences from Telugu language. Also this study will be helpful in developing other Natural Language Processing (NLP) applications like converting a compound sentence in simple sentences, grammar checking of compound sentences.


1. Sanjeev kumar Sharma, G.S Lehel ‘Identification of Compound Sentences in Punjabi Language’ Research Cell: An International Journal of Engineering Sciences, InauguralIssue2010ISSN: 2229-6913 (Print), ISSN: 2320-0332 (Online) Vol. 1, pp. 1-8.

2. Beesley, K. R. 2001. Finite-state morphological analysis and generation of Arabic at Xerox Research: Status and plans in 2001. In ACL Workshop on Arabic Language Processing: Status and Perspective Vol. 1, pp. 1-8.

3. Bharati, A., Chaitanya, V., Sangal, R., & Ramakrishnamacharyulu, K. V. 1995. Natural language processing: a Paninian perspective. New Delhi: Prentice-Hall of India. pp. 65-106.

4. Bigert, J., Kann, V., Knutsson, O., & Sjobergh, J. 2004. Grammar checking for Swedish second language learners. pp. 33-47.

5. Bustamante, F. R., & Le6n, F. S. 1996. GramCheck: A grammar and style checker. In Proceedings of the 16th conference on Computational linguistics-Volume 1. Association for Computational Linguistics. pp. 175-181

6. Carlberger, J., Domeij, R., Kann, V., & Knutsson, O. 2004. The development and performance of a grammar checker for Swedish: A language engineering perspective. Natural language engineering, 1(1).

7. Chidambaram, D. 2005. Processing complex sentences for information extraction. A Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science.

8. Ehsan, N., & Faili, H. 2010. Towards grammar checker development for Persian language. IEEE International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE), 2010. pp. 1-8

9. Fernandes, E. R., Pires, B., dos Santos, C. N., & Milidiiu, R. L. 2009. Clause identification using entropy guided transformation learning. IEEE 2009 Seventh Brazilian Symposium in Gill, M. S., Lehal, G. S., & Joshi, S. S. 2009. Part of speech tagging for grammar checking of Punjabi. The Linguistic Journal, 4(1), pp. 6-21.

10. Information and Human Language Technology (STIL), pp. 117-124.

11. Hein, A. S. 1998. A Chart-Based Framework for Grammar Checking Initial Studies. In Proc. of 11 th Nordic Conference in Computational Linguistic. pp. 68-80.

12. Jurafsky, Daniel and James H. Martin. 2000. Speech and Language Processing: An Introduction to Natural language Processing, Computational Linguistics, and Speech Recognition. Pearson Education, Delhi, India

13. Kubon, V., & Platek, M. 1994. A grammar based approach to a grammar checking of free word order languages. In Proceedings of the 15th conference on Computational linguistics-Volume 2. Association for Computational Linguistics. pp. 906-910

14. Naber, D. 2003. A rule-based style and grammar checker. Thesis, Technical Faculty, University of Bielefeld, Germany

15. Narula, R., & Sharma, S. K. 2014. Identification and Separation of Simple, Compound and Complex Sentences in Punjabi Language. International Journal of Computer Applications & Information Technology. Vol. 6, Issue II Aug-September 2014.

16. Parveen, D., Sanyal, R., & Ansari, A. 2011. Clause Boundary Identification using Classifier and Clause Markers in Urdu Language. Polibits Research Journal on Computer Science, 43, pp. 61-65.





NLP, Compound Sentences, Independent clause, Dependent clause.

  • Format Volume 4, Issue 2, No 2, 2016
  • Copyright All Rights Reserved ©2016
  • Year of Publication 2016
  • Author V.Suresh, M.S.Prasad Babu
  • Reference IJCS-122
  • Page No 721-726

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